Introduction

The COVD-19 pandemic has led to major impacts on transmission of communicable diseases1,2,3,4,5. There is evidence that pandemic measures reduced social contact leading to substantial reductions in the incidence of influenza, respiratory syncytial virus, and other respiratory viral illnesses from 2020 to 20226,7. Whether such measures have impacted M. tuberculosis transmission is unknown and no study has investigated M. tuberculosis transmission levels before and after the start of the COVID–19 pandemic. Despite this, there is broad agreement that M. tuberculosis transmission trends are likely to have important implications for future tuberculosis disease trends8.

Although tuberculosis diagnoses declined in most countries during the COVD-19 pandemic (from 2020 onwards), the impact of the pandemic on Mycobacterium tuberculosis transmission—which is driven primarily through person-to-person contact—at the population-level is debated1,2,8,9,10,11,12. At least two opposing forces may impact M. tuberculosis transmission due to the COVID–19 pandemic7. First, substantial delays in tuberculosis diagnosis due to COVID–19 containment strategies are likely to lead to further transmission from people with disease to their social networks. Second, broad non-pharmaceutical interventions (e.g., social distancing, quarantine, increased mask use, etc.) may decrease tuberculosis exposure and transmission at the community-level1,13. Still others have suggested that household transmission may increase due to more time spent in households (e.g., from self-quarantine and social distancing) while community transmission may decrease. However, no study has investigated M. tuberculosis transmission levels before and after the start of the COVID–19 pandemic.

To address this knowledge gap, we pooled data from annual, population-based sample of adolescents administered tuberculin skin tests in more than 1400 schools from 12 cities in eastern China from 2017 to 2021. We also evaluated weekly tuberculosis notifications in the province from 2017 to 2021 to assess longer-term trends of tuberculosis diagnoses after the pandemic.

Results

School data

During the study period, 1,940,735 adolescents were administered a tuberculin skin test, representing 1427 schools in 12 cities (Table 1; Table S1–3; Fig. S1). Figure 1 presents the geographic distribution of school and adolescent participation in tuberculin skin test screening. The number of schools participating in screening ranges from 3 to 47, and there is substantial heterogeneity in screening scale across counties, ranging from 499 adolescents in Guangling District to 98,804 in Binhai County. The number of adolescents administered tests increased with time from 118,831 (Nschools = 311) in 2017 to 734,709 (Nschools = 1186) in 2021 (Table 1). More schools reported indurations cutoffs from students of 15 mm (Nparticipants = 1,922,046) compared to 10 (Nparticipants = 1,196,265) and 5-mm induration cutoffs (Nparticipants = 1,653,995).

Fig. 1: Geographic distribution of participating schools and schoolchildren by study area from 2017 to 2021.
figure 1

This figure presents a choropleth map illustrating the number of participating schools (A) and the total number of schoolchildren (B) across various administrative regions within the study area for the period 2017–2021. Data are categorized into distinct numerical ranges and represented by color intensity, allowing for a visual assessment of participation density and potential spatial disparities. A specifically highlights the distribution of participating schools, with shades of blue, orange, and red indicating increasing numbers of schools (1–9, 10–19, 20–29, 30–39, and 40+, respectively). B mirrors this approach for the schoolchildren, employing a similar color gradient to denote the number of students (1–9999, 10,000–19,999, 20,000–29,999, 30,000–39,999, and 40,000+). Regions marked in gray indicate unavailable data. Data were compiled from annual monitoring records and correspond to the total cumulative participation over the study period. The map is sourced from the National Geographic Information Public Service Platform (https://cloudcenter.tianditu.gov.cn/administrativeDivision). The review number of the map is GS(2024)0650.

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Table 1 Description of participating schoolchildren and schools included in annual tuberculin surveys from 2017 to 2021, Jiangsu Province, China
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Among middle school students, the overall prevalence of tuberculin skin test positivity at 5, 10, and 15 mm cutoffs was 8.2% (95% CI, 8.1–8.2), 3.4% (95% CI, 3.4–3.5), and 1.1% (95% CI, 1.1–1.1), respectively. Among high school students, prevalence at each cutoff was 11.0% (95% CI, 10.9–11.0), 4.6% (95% CI,4.6–4.7), and 1.6% (95% CI, 1.6–1.6), respectively (Tables S4–8).

Overall, we found a reducing prevalence of tuberculin positivity across years of follow-up with decreases occurring during pandemic years, regardless of millimeter induration cutoff (Fig. 2). Among middle school students, the prevalence of tuberculin positivity using a 5 mm induration cutoff was relatively consistent from 2017 to 2019 (9.3% [95% CI, 8.9–9.7], 9.6% [95% CI, 9.3–9.8], 10.2% [95% CI, 9.9–10.4], respectively), but was largely reduced in 2020 and 2021 (8.0% [95% CI, 7.9–8.2] and 7.0% [95% CI, 6.9–7.1]). The percentage prevalence reduction in 2020 and 2021 compared to the expected value was 23.8% (95% PI, −26.6, −20.8) and 36.4% (95% PI, −39.1, −32.7), respectively. From 2017 to 2019, the annual risk of M. tuberculosis infection among middle school students was 7.8, 8.0, and 8.5 infections per 1000 persons (Table 2). In 2020 and 2021, the annual risk of M. tuberculosis infection decreased to 6.7 and 5.8 infections per 1000 persons, respectively. There was a 24.7% (95% PI, −27.2, −21.2) and 37.0% (95% PI, −40.8, −33.3) decreased percentage change in the annual risk of M. tuberculosis infection in 2020 and 2021 compared to the counterfactual model. Among high school students, similar but slightly more modest reductions in tuberculin positivity were seen in post-pandemic years. For example, the prevalence of tuberculin positivity in pre-pandemic years was 11.9% (95% CI, 11.7–12.2), 12.1% (95% CI, 11.9–12.3), and 11.8% (95% CI, 11.7–12.0), respectively. In 2020 and 2021, prevalence was 11.6% (95% CI, 11.5–11.7) and 9.6% (95% CI, 9.5–9.7). In 2020 and 2021, there was a reduction in the annual risk of M. tuberculosis infection of 2.5% (95% PI, −6.5, 1.8) and 19.8% (95% PI, −24.0, −14.5) compared to each respective counterfactual model.

Fig. 2: Annual tuberculin skin test percent prevalence from 2017 to 2021 in Jiangsu Province, China.
figure 2

Graph displays the annual percent prevalence of tuberculin skin test positivity at differing millimeter cutoffs for each year from 2017 to 2021 in Jiangsu Province, China. Each point for each year represents the number of students tested during that year in representative schools. Therefore, the denominator for each year may be distinct. Millimeter cutoffs can be seen for 5 mm (left top panel), 10 mm (right top panel), and 15 mm (bottom panel). The gray shaded area on the right is the time period in which Covid-19 restrictions were put in place in Jiangsu Province (starting in February 2020). Gray circles represent the observed percent prevalence of tuberculin skin test positivity during each year of testing in the included cities. The solid red line represents the fitted model of the observed percent prevalence data from pre-COVID (January 2017 to January 2020) and post-COVID (February 2020 to December 2021). The blue dotted line represents the counterfactual expected percent prevalence of tuberculin skin test positivity during the post-COVID time period based on the observed data from the pre-COVID time period. The red transparent shaded area for the observed values represents 95% confidence intervals. The blue transparent shaded area for the predicted values represents 95% confidence intervals from the counterfactual fitted models.

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Table 2 Interrupted time-series analyses of predicted versus observed tuberculin positivity (5 mm induration) and annual risk of tuberculosis infection from middle and high school students, 2017–2021
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When using alternative millimeter cutoffs, we consistently found decreases in the annual risk of M. tuberculosis infection in 2021 compared to counterfactual estimates (Fig. 3; Table S5; Table S7). Using a 10 mm cutoff, there was a 27.7% (95% PI, −39.4, −10.5) reduction in the annual risk of M. tuberculosis infection among high school students and a non-significant 32.2% (95% PI, −55.2, 37.0) decrease among middle school students (Table S5). When using a 15 mm induration cutoff, the estimated percentage reduction in the annual risk of M. tuberculosis infection in 2020 and 2021 among middle school students was 23.6% (95% PI, −40.8, 7.5) and 39.9% (95% PI, −58.5, 9.1). Among high school students, the percentage reduction in the annual risk of M. tuberculosis infection in 2020 and 2021 was 7.4% (95% PI, −8.7, −6.1) and 30.4% (95% PI, −31.7, −29.0) compared to the expected model (Table S7).

Fig. 3: Percentage reduction in the observed annual risk of Mycobacterium tuberculosis infection in 2020 and 2021 compared to expected values in an interrupted time-series analysis.
figure 3

The figure presents the observed percentage reduction in the annual risk of Mycobacterium tuberculosis infection for 2020 and 2021 among middle school and high school students compared to predicted values based on historic data from 2017 to 2019. The annual risk of M. tuberculosis infection was calculated by transforming the percent prevalence of tuberculin positivity in each measured year as described in the methods. The mean age of middle school students was 12.5 years and high and school students was 15.5 years. All participants from each year were included in this specific presented analysis. Other analyses included only schools with full data on all years and are presented in Supplementary Tables 4, 6 and 8. They were broadly consistent with these results.

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When restricting our population to only schools with complete annual survey data in all years, our results were broadly consistent (Table S4; Table S6; Table S8). Using a 5 mm induration, there was a 48.6 (95% PI, −55.7, −39.0) and 19.9 (95% PI, −29.5, −7.5) percentage reduction in the annual risk of M. tuberculosis infection among middle and high school students in 2021. Using a 10 mm induration, this percentage reduction in 2021 was 9.9 (95% PI, −10.1, −9.7) among high school students and no statistically significant reduction among middle school students. Using a 15 mm induration, there was a non-statistically significant percentage reduction in 2021 of 42.7 (95% PI, −62.1, 16.4) among high school students compared to the counterfactual model.

We performed several sensitivity analyses. First, we estimated the number of new student entries in participating schools from the 12 cities; we found that this number remained largely consistent over the study time period (Fig. S2). The mean number of student entries per school was also similar over time. In 2017, the mean number of student entries per school was 341 (95% CI, 314–368), similar to the mean school entries in 2019 (371; 95% CI, 353–389) and 2021 (370; 95% CI, 354–386). This suggests that the number of students entering school was not substantially altered pre- and post-pandemic. Second, we conducted a quantitative bias analysis considering the sensitivity and specificity of the tuberculin skin test and potential influence on annual trends in tuberculin skin test positivity. When adjusting for diagnostic characteristics of the tuberculin skin test, we found relatively similar adjusted versus observed proportions in 2017 (11.1% versus 11.0%), 2018 (11.5% versus 11.4%), and 2019 (11.5% versus 11.4%). Adjusted proportions were reduced compared to observed proportions in 2020 (10.1% versus 10.4%) and 2021 (8.7% versus 7.7%).

In most cities, we found that a decreasing trend in tuberculin positivity was seen in 2020 and 2021 (compared to 2019). However, this was not the case for schools in every city. For example, decreasing trends were seen in Lianyungang, Nantong, Suzhou, Wuxi, amongst others. However, we did not see decreasing trends in Changzhou, Huaian, and others (Table S9; Table S10), suggesting there was some city-level heterogeneity in our findings.

Tuberculosis disease notification data

In total, there were 149,970 tuberculosis diagnoses in the province from 2017 to 2021. The absolute number of tuberculosis diagnoses ranged from 28,379 (2365 per month) in 2017 to 22,827 (1902 per month) in 2021 (Fig. S3).

We compare key characteristics of students and schools tested in each time period (2017–2019 and 2020–2021). These 12 cities are located in different parts of Jiangsu Province, north, central, and south, and have different incidence rates of tuberculosis and characteristics, which is also the case in this study (Table S11; Table S12).

Overall, provincial tuberculosis case notifications dropped 23% (95% PI, 18–27) in the first 4 months of 2020 compared to the counterfactual model (5666 observed versus 7319 expected notifications) (Fig. S4, left panel). However, observed notifications quickly rebounded and by the end of 2020 there was no statistical reduction in observed cases per month (2029 observed versus 2085 expected notifications [95% PI, 1944–2227]; –2.7% change, 95% PI, –4.4, 8.9). There continued to be no statistical reduction in observed versus expected notifications in 2021 (1902 observed versus 2004 expected notifications [95% PI, 1801–2207]; –5.1% change, 95% PI, –13.0, 5.6). The notification rate followed a similar trend as the absolute number of notifications (Fig. S4, right panel). There was a significant drop in the observed tuberculosis notification rate in the first months of 2020 followed by a rebound to the expected values found through the counterfactual model.

Discussion

Using data from over 1.9 million adolescents who underwent tuberculin skin tests from 2017 to 2021 in eastern China, this study provides strong empirical evidence that M. tuberculosis transmission may have declined after the start of the COVID-19 pandemic in China. We estimated a significant reduction in the annual risk of M. tuberculosis infection in 2020 and 2021 compared to what was expected using historical data. Reductions in the annual risk of M. tuberculosis infection were greater in 2021 compared to 2020. Lastly, we found that, although there was a 23% drop in tuberculosis notifications in the first four months of 2020 in Jiangsu Province, this drop was short-lived, and the tuberculosis control program quickly rebounded.

There has been considerable debate about the impact of the COVID-19 pandemic on M. tuberculosis transmission. Some researchers have hypothesized that M. tuberculosis transmission may have increased post-20202,14, while others have postulated net decreases12,15. Still others have suggested that household transmission may increase due to more time spent in households (e.g., from self-quarantine and social distancing) while community transmission may decrease1,16. Our results suggest that, among adolescents in China, there has been a 30–40% decrease in the annual risk of M. tuberculosis infection, a measure of tuberculosis transmission. We found slightly more modest reductions in the annual risk of infection among high school compared to middle school students; reasons for this are not clear from our data but may be potentially attributable to differences in social contact patterns. Assortative age mixing among older adolescents (compared to younger populations) may be one potential driver of this finding; a further understanding of age-related social mixing in this population is needed. Importantly, our analysis only includes adolescents and does not include adults or young children. Most M. tuberculosis transmission occurs outside of households17,18,19, especially as age increases19. Therefore, reductions in the annual risk of M. tuberculosis infection may be even higher in older groups compared to our study population.

Although this finding may be generalizable to adolescent populations in other areas of China, its transferability to other countries is unclear. China has had a unique COVID-19 pandemic control strategy, with short-term lockdowns of entire cities, strict quarantine, and widespread mask use. The Zero COVID policy was implemented to the same degree during the post-intervention period. All individuals follow the national guidelines for the prevention and control of the novel coronavirus. Therefore, the prevention and control strategies of each city in Jiangsu Province are essentially the same. Changes in M. tuberculosis transmission rates during the pandemic are likely largely reliant on local dynamics20 and whether such reductions are seen in other settings outside of China needs further investigation.

Tuberculosis diagnoses have decreased considerably during the COVID-19 pandemic however, the severity of underdiagnoses of tuberculosis has been largely heterogenous from country-to-country. For example, in Vietnam, there was a small 8% reduction to tuberculosis notifications in 2020 compared to 201921. Other countries have had short-term impact as large as 30–50%1,22. In Jiangsu Province, tuberculosis notifications dropped 30% in early 2020 compared to 2015–201923; similar trends have been observed throughout China16. Our finding of a rebound in tuberculosis notifications to expected values is important and may suggest that it is possible for tuberculosis control programs to recover from initial catastrophic healthcare impact of the pandemic. Multiple avenues—not only M tuberculosis transmission rates—may impact the tuberculosis burden.

The strengths of our study include the large sample size, comprising almost two million adolescents tested, allows us to estimate the M. tuberculosis transmission burden at the population level, and serial surveys over a 5-year time span. M. tuberculosis infection prevalence rates vary by age, with increasing prevalence with age24,25,26. Our tuberculin surveys included the same age population measured over time—therefore, differences in the prevalence and the annual risk of M. tuberculosis infection are not confounded by age27. Participants in our tuberculin surveys were a non-selected population and therefore these annual samples are likely to be a reasonable representation of transmission trends in the general population. Despite these strengths, QuantiFERON or tuberculin conversion may be a more direct measure of M. tuberculosis transmission28,29.

We used distinct induration cutoffs to indicate a positive TST, which might over or underestimate M. tuberculosis infections. We used different cutoffs to account for potential misclassification (finding similar results). The use of QuantiFERON testing might have limited bias from boosting however, the need for blood samples over a large population, laboratory testing, and the cost involved are not feasible.

Our findings should be interpreted within the context of several limitations. First, boosting of tuberculin skin tests may occur from BCG vaccination, which is universally given at birth in China30,31,32. However, this bias is unlikely to affect our results as BCG does not impact tuberculin skin testing 5–10 years after administration33,34. Second, selection bias may be present in our study population if a large proportion of children did not attend school during pandemic years or children that did attend school during the pandemic were of higher socioeconomic status than children not attending school. However, this hypothesis is not supported by our data which indicated that the number of new student entries per school remained consistent throughout the study period. Third, in our time-series analyses, we applied a before/after cutoff point from the first implementation of non-pharmaceutical interventions (starting in January 2020). These community-wide interventions have continued at varying intensities. Fourth, we acknowledge the possibility that a student may be present in both the middle and high school tuberculin testing and therefore earlier and later years during the study period. If present, this would not bias the analysis that is restricted to just middle or high schools; but this may theoretically bias the analysis grouping all types of schools. Fifth, we note that aggregation bias from certain cities may be present in this analysis (i.e., certain cities may be driving these results more than others. Finally, we were limited in including predictors within our model as they were likely affected by the pandemic. Including predictors in our regression model that were influenced by the pandemic would lead to biased counterfactual estimates.

In summary, we found large reductions in M. tuberculosis transmission post-pandemic among adolescents in a medium-burden province in China. Generally, reductions were larger in 2021 compared to 2020. Nonpharmaceutical, pandemic-specific interventions, such as widespread use of masks and face coverings, physical distancing, and quarantine, may have reduced M. tuberculosis transmission at the population level.

Methods

Study setting, study design, and sample population

We conducted serial tuberculin surveys investigating the annual prevalence of tuberculin skin test positivity in Jiangsu Province, China. In China, approximately 5% of tuberculosis cases occur among students, most of which occur above 15 years of age. In the past 10 years, the incidence of tuberculosis in Jiangsu Province has decreased significantly. In the province, since the initial COVID-19 outbreak in early 2020, there have been continuously adjusted measures and strategies for the prevention and control of the COVID-19 pandemic. This has ranged from a Zero-clearance policy to a dynamic Zero-clearance policy, which continued until December 2022, the end of the study period (Tables S13, 14).

This project was approved by the Institutional Review Board of Jiangsu Provincial Center for Disease Control and Prevention (B010-01). Schools that meet national school guidelines and conducted tuberculin testing during one of the study period years are included in this study. Schools were not selected based on risk profile or any specific school characteristic. For inclusion in the study, a school needed to have implemented TST screening during one of the study period years. We collected two sets of data. First, non-selected schoolchildren from 12 prefecture-level cities in Jiangsu Province were administered tuberculin skin tests at middle and high school entry from 2017 to 2021. Second, we obtained weekly tuberculosis notifications and notification rates (among all ages) in the province overall from 2017 to 2021.

This study was approved by the Ethics Committee of Jiangsu Center for Disease Control and Prevention. Written informed consent was obtained from study participants (JSJKB010-01). Prior to these screenings among new entry students, a notification is issued that requires signatures and consent from both students and parents (Supplementary Information-Further Methodological Information).

Data sources

Starting in 2017, annual screening for M. tuberculosis infection (through tuberculin skin testing) at school inception was performed as a component of a comprehensive physical examination in school districts across Jiangsu Province. According to the Guidelines for Tuberculosis Prevention and Control in Chinese Schools (https://www.gov.cn/zhengce/zhengceku/2020-12/05/content_5567137.htm.), tuberculin skin test is performed using protein purified derivative (PPD) through the Mantoux method. According to these guidelines, after 48–72 h, the transverse and longitudinal diameters of induration should be measured, and the average diameter of the induration should be recorded (calculated as the sum of the transverse and longitudinal diameters, divided by two).

Physical examinations were typically performed by trained school nurses between September and October of every year, which included examinations of blood biochemical, and other examinations. Participants in tuberculin surveys were a non-selected population with no clinical indication for participant testing; all children in selected schools were tested. Schools were selected at random for inclusion into the program. Schoolchildren were tested at middle school entry were between 12 and 13 years of age; participants tested at high school entry were between 15 and 16 years of age. A person with a strongly positive (induration diameter≥15 mm) reactive tuberculin skin test was subsequently screened for tuberculosis with a second full physical examination, chest X-ray, and/or referral to a tuberculosis-designated hospital if clinically indicated. Test results are reported to the provincial CDC at the school-level by the millimeter induration cutoff used (5 mm, 10 mm, and/or 15 mm).

To evaluate the potential for selection bias, whereby schoolchildren may not attend school due to the COVD-19 pandemic either due to illness (although there have been very few diagnosed childhood cases of COVD-19 in the province), fear of illness, or other reasons, we collected the mean number of new student entries per school for each of the participating schools over time. Students entering either middle or high school are the population eligible for tuberculin testing through the provincial program and therefore increases or decreases over time in this number may represent possible selection bias. Students in schools with a combined middle and high school followed the same testing protocol; testing occurred at middle school entry and then at high school entry.

We also obtained weekly tuberculosis notifications from January 2017 to December 2021 among all ages in the province. Tuberculosis is a reportable disease in China, and all persons diagnosed with tuberculosis are managed in a tuberculosis registry run by the Jiangsu Provincial CDC23. Because of this, patient diagnoses can be tracked at a city- and provincial level over time.

Statistical analysis

We analyzed these two sources of data (tuberculin surveys and tuberculosis notifications) over time. We tracked weekly tuberculosis notifications and notification rates. We defined a positive tuberculin skin test as above or equal to an induration of 5 mm and performed secondary analyses using 10 mm, and 15 mm induration cutoffs. We classified the beginning of COVD-19-related non-pharmaceutical interventions as the first occurrence of the provincial-wide quarantine (24 January 2020).

We conducted interrupted time-series analyses using generalized linear models to compare trends in both data sources before and after policy restrictions due to the COVD-19 pandemic. We compared observed trends from all outcomes before February 2020 to a counterfactual model assuming background trends prior to the implementation of COVID–19-related restrictions continued linearly. Each model estimated the epidemiological trend of each indicator (notification rate, absolute number of notifications, and the prevalence of tuberculin skin test positivity at differing cutoffs) based on historical data before February 2020. These models were used as comparisons with the actual observed outcome data to give a counterfactual estimation of expected activity if the COVID–19 non-pharmaceutical interventions had not been implemented. For notification outcomes, we included a binary variable to account for well-recognized holidays to account for underreporting in the data during certain time periods. Absolute and relative changes were calculated for each indicator during 2020 and 2021 compared with counterfactual models. Prediction intervals (PIs) at the 95% level presented for percentage change.

We calculated the annual risk of M. tuberculosis infection by transforming the prevalence of tuberculin positivity in each measured year using standard formulas27,35,36,37,38. We incorporated mean age to account for the number of years of exposure of individuals using the following formula:

$${{\rm{Annual}}}\; {{\rm{risk}}}\; {{\rm{of}}}\; {{\rm{infection}}}=1{-}{(1{-}{{\rm{Prevalence}}})}^{1/{{\rm{mean}}}\; {{\rm{age}}}}$$

Tuberculin surveys were conducted at two distinct ages (12–13 and 15–16 years of age). As such, we calculated the annual risk of M. tuberculosis infection separately for middle and high schools. We included students in schools with a combined middle and high school in overall calculations, but not for separate stratified calculations by middle and high school. For calculations of the annual risk of M. tuberculosis infection, we assumed that the mean age of middle school students was 12.5 and high and school students was 15.5. We validated this assumption by randomly selecting 5000 new entry students (1000 students per year; half of whom were middle school and half high school students) from 2017 to 2021 across five cities in Jiangsu Province.

To assess the potential of selection bias post-pandemic (2020–2021), we analyzed new student school entries over time. We compared the median and mean number of new school entries per school from 2017 to 2021 and calculated conservative binomial-based exact confidence intervals to evaluate uncertainty.

All analyses were conducted with Stata (version 17.1).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.